1. Field of the Invention
The present invention generally relates to component based business models and, more particularly, to a system and method for deducing and resolving potential inconsistencies in the semantic representation of component business model maps.
2. Background Description
Component Business Modeling is a state-of-art technology for modeling the entire enterprise from a business perspective, driving information technology (IT) solutions to help transform an enterprise from a current AS-IS condition to a desired TO-BE condition. The component business model (CBM) map is the key component in CBM methodology and CBM related tools. Component business modeling is a technique for modeling businesses based on a number of non-overlapping “business components,” which are defined as relatively independent collections of business activities. It provides simple business views for analysis, unlike traditional business process-based models which provide transactional views of businesses. The CBM methodology facilitates qualitative analysis techniques such as the dependency analysis (to identify “hot” components associated with business pain points), the heat map analysis (also to identify “hot” components associated with business pain points), and the overlay analysis (to identify IT shortfalls of the “hot” components).
The CBM-based qualitative business analysis has been mostly conducted manually by business consultants. What is needed for automation of the CBM-based business analyses is a semantic representation of the component business model. In particular, there is a need to validate the CBM models by detecting inconsistencies 1) among the various CBM maps (that is, the universal CBM map at the broadest level, the intermediate level industry CBM maps, and the CBM maps for particular enterprises) and 2) between the CBM meta-model and a CBM map.
Some examples of inconsistency are as follows. Suppose the demand forecast and analysis component belongs to the marketing competency in the CBM map for the retail industry. But a consultant working on a CBM map for an enterprise within the retail industry may assign the demand forecast and analysis component to a different competency, say, financial management. Then the enterprise map is inconsistent with the retail industry map, but the consultant has no systematic methodology for identifying this kind of inconsistency.
Another simple example would be the cardinality inconsistency. For instance, the CBM meta-model specifies that a component has one and only one accountability level. When working on a CBM map, a consultant may give a component more than one accountability level. This is not correct and will complicate further analysis, but the consultant may not be aware of the inconsistency because of the large number of components, activities or services in one CBM map.
Inconsistencies in CBM maps will set traps that will compromise the efficiency of further CBM related consulting. The manual validation of CBM models and maps in order to avoid these inconsistencies is a tedious and error-prone process, causing significant degradation of productivity and accuracy of the CBM-based analysis. Therefore, some methods or tools should be developed to detect those inconsistencies as early as possible.